Web Intelligence and Agent Systems: An International Journal is an official journal of Web Intelligence Consortium (WIC), an international organization dedicated to promoting collaborative scientific research and industrial development in the era of Web and agent intelligence. WIAS seeks to collaborate with major societies and international conferences in the fields. Presently, it has established a tie with the International Conference on Web Intelligence and the International Conference on Intelligent Agent Technology. WIAS is a peer-reviewed journal, which publishes 4 issues a year, in both electronic and hard copies.

WIAS aims to achieve a disciplinary balance between Web technology and intelligent agent technology. It is committed to deepening the understanding of computational, logical, cognitive, physical, and social foundations as well as the enabling technologies for developing and applying Web-based intelligence and autonomous agents systems. The journal features high-quality, original research papers (including state-of-the-art reviews), brief papers, and letters in all theoretical and technology areas that make up the field of WIAS.

Abstract: Taste in music is of highly subjective nature, making the recommending of music tracks a challenging research task. With TRECS, our live prototype system, we present a weighted hybrid recommender approach that amalgamates three diverse recommender techniques into one comprehensive score. Moreover, our prototype system peppers the generated result list by some simple serendipity heuristic. This way, users can benefit from recommendations aligned with their current taste in music while gaining some exploratory diversification. Empirical evaluations of the live TRECS system, based on an online evaluation, assess the overall recommendation quality as well as the impact of each of the…three sub-recommenders. In addition, to better understand the nature and impact of serendipity in isolation, we conducted another study with another recommender prototype of ours, named SONG STUMBLER. The latter assesses three different serendipity metrics in an online evaluation.
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Abstract: Personality can be defined as a set of characteristics which makes a person unique. Psychological theory suggests that people's behavior is a reflection of personality. Therefore, it is feasible to predict personality through behavior. Conventional personality assessment is performed by self-report inventory. Participants need to fill in a tedious inventory to get their personality scores. In the large-scale investigation, every returned inventory needs manual computation, which costs much manual efforts and cannot be done in real time. In order to avoid these shortages, this research aims to objectively predict the Big-Five personality from the usage records of Sina Microblog. Since…its initial launch in December, 2005, Sina Microblog has been the leading microblogging service provider in China. Millions of users upload and download resources via microblogging status everyday. Therefore, by conducting an online user survey of 444 active users, this paper analyzes the relation modes between personality and online behavior. Furthermore, this research proposes multi-task regression and incremental regression to predict the Big-Five personality from online behaviors. The results indicate that correlation factors are significant between different personality dimensions. Besides, our training data set is reliable enough and multi-task regression performs better than other modeling algorithms.
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Abstract: In task environments with large state and action spaces, the use of temporal and state abstraction can potentially improve the decision making performance of agents. However, existing approaches within a reinforcement learning framework typically identify possible subgoal states and instantly learn stochastic subpolicies to reach them from other states. In these circumstances, exploration of the reinforcement learner is unfavorably biased towards local behavior around these subgoals; temporal abstractions are not exploited to reduce required deliberation; and the benefit of employing temporal abstractions is conflated with the benefit of additional learning done to define subpolicies. In this paper, we consider a…cognitive agent architecture that allows for the extraction and reuse of temporal abstractions in the form of experience trajectories from a bottom-level reinforcement learning module and a top-level module based on the BDI (Belief-Desire-Intention) model. Here, the reuse of trajectories depends on the situation in which their recording was started. We investigate the efficacy of our approach using two well-known domains – the pursuit and the taxi domains. Detailed simulation experiments demonstrate that the use of experience trajectories as plans acquired at runtime can reduce the amount of decision making without significantly affecting asymptotic performance. The combination of temporal and state abstraction leads to improved performance during the initial learning of the reinforcement learner. Our approach can significantly reduce the number of deliberations required.
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Abstract: Modelling the temporal dynamics of personal preferences is still under-developed despite the rapid development of personalization. In this paper, we observe that the user preference styles tend to change regularly following certain patterns in the context of movie recommendation systems. Therefore, we propose a Preference Pattern model to capture the user preference styles and their temporal dynamics, and apply this model to improve the accuracy of the Top-N movie recommendations. Precisely, a preference pattern is defined as a set of user preference styles sorted in a time order. The basic idea is to model user preference styles and their temporal…dynamics by constructing a representative subspace with an Expectation-Maximization (EM)-like algorithm, which works in an iterative fashion by refining the global and the personal preference styles simultaneously. Then, the degree which the recommendations match the active user's preference styles, can be estimated by measuring its reconstruction error from its projection on the representative subspace. The experiment results indicate that the proposed model is robust to the data sparsity problem, and can significantly outperform the state-of-the-art algorithms on the Top-N movie recommendations in terms of accuracy.
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Abstract: We present an agent architecture and a hybrid behavior learning method for it that allows the use of communicated intentions of other agents to create agents that are able to cooperate with various configurations of other agents in fulfilling a task. Our shout-ahead architecture is based on two rule sets, one making decisions without communicated intentions and one with these intentions, and reinforcement learning is used to determine in a particular situation which set is responsible for the final decision. Evolutionary learning is used to learn these rules. Our application of this approach to learning behaviors for units in a…computer game shows that the use of shout-ahead using only communicated intentions in the second rule set substantially improves the quality of the learned behavior compared to agents not using shout-ahead. Also, allowing for additional conditions in the second rule set can either improve the quality or worsen it, based on what type of conditions are used.
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Abstract: Fervent and agile communication on social networking sites and in virtual organizations provides opportunities for potential issues to trigger individuals into individual action as well as the attraction and mobilization of like-minded individuals into an organization that is both physically and virtually emergent. Examples are the rapid pace of Arab Spring and the diffusion rate of the occupy movement. Previous organizational models lack the representational power to model spontaneous exigencies of a network organization that accounts for rapid rates of dissemination in impromptu networks. This model, therefore, is conceived in a life cycle for a prototypical, emergent networked organization and…description of operations therein from formation to dissolution. After describing the life cycle, this article offers insights for a model of a successful emergent organization and an implemented example of a spacecraft organization of satellites.
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